TY - GEN
T1 - Estimation of Permanent Magnet Demagnetization Using MRAS with no Sensitivity to Winding Resistance of IPM Motor
AU - Husnayain, Faiz
AU - Noguchi, Toshihiko
AU - Iwama, Kiyohiro
AU - Sudiarto, Budi
AU - Yusivar, Feri
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Accurate parameter estimation is crucial for the optimal operation and control of interior permanent magnet (IPM) motors. This study proposes a parameter identification technique for permanent magnet (PM) flux linkage utilizing a hybrid approach, combining a finite element method (FEM)-based 3D-Inductance map and a model reference adaptive system (MRAS) based on instantaneous reactive power. Considering the cross-coupling effect, the objective is to improve the control output performance by reducing transient response errors and conducting PM flux linkage identification under magnetic saturation. The proposed parameter estimation method is robust and fast to adapt to dynamic motor operation and, simultaneously, online and able to determine the PM flux linkage. The FEM-based map provides a comprehensive model of the IPM motor by considering the spatial variation of inductances across the motor cross-section. The MRAS utilizes the reactive power component of the motor to estimate the PM flux linkage by comparing the measured and estimated instantaneous reactive power. By comparing the output of the reference model with the actual motor response, the MRAS algorithm adapts the estimated parameters to minimize the error between the two. This study proposed the reactive power component as it has no sensitivity with resistance. So, the impact of motor operation, which lead to heat production and variation of winding resistance, will not affect the proposed method. As a result, the parameter mismatches due to PM demagnetization and magnetic saturation are significantly reduced.
AB - Accurate parameter estimation is crucial for the optimal operation and control of interior permanent magnet (IPM) motors. This study proposes a parameter identification technique for permanent magnet (PM) flux linkage utilizing a hybrid approach, combining a finite element method (FEM)-based 3D-Inductance map and a model reference adaptive system (MRAS) based on instantaneous reactive power. Considering the cross-coupling effect, the objective is to improve the control output performance by reducing transient response errors and conducting PM flux linkage identification under magnetic saturation. The proposed parameter estimation method is robust and fast to adapt to dynamic motor operation and, simultaneously, online and able to determine the PM flux linkage. The FEM-based map provides a comprehensive model of the IPM motor by considering the spatial variation of inductances across the motor cross-section. The MRAS utilizes the reactive power component of the motor to estimate the PM flux linkage by comparing the measured and estimated instantaneous reactive power. By comparing the output of the reference model with the actual motor response, the MRAS algorithm adapts the estimated parameters to minimize the error between the two. This study proposed the reactive power component as it has no sensitivity with resistance. So, the impact of motor operation, which lead to heat production and variation of winding resistance, will not affect the proposed method. As a result, the parameter mismatches due to PM demagnetization and magnetic saturation are significantly reduced.
KW - IPM motor
KW - magnetic saturation
KW - MRAS
KW - no resistance sensitivity
KW - parameter estimation
KW - PM demagnetization
UR - http://www.scopus.com/inward/record.url?scp=85183316509&partnerID=8YFLogxK
U2 - 10.1109/ITECAsia-Pacific59272.2023.10372202
DO - 10.1109/ITECAsia-Pacific59272.2023.10372202
M3 - Conference contribution
AN - SCOPUS:85183316509
T3 - ITEC Asia-Pacific 2023 - 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific
BT - ITEC Asia-Pacific 2023 - 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2023
Y2 - 28 November 2023 through 1 December 2023
ER -